With the increasing availability of big data in every field of science, the
development of visual collecting tools able to simplify the interpretation of such
quantity of data is essential. However, many scientists do not have a specific concept of
data visualization, manifesting serious problems in implementing it, especially for
omics data. Thus, bioinformatics specialists continuously develop new algorithms and
tools to perform the deepest analysis of these data, along with innovative methods to
simplify their output representation.
In this work, we evaluated a set of free tools that we considered highly suitable for
enhancing the interpretation of next-generation sequencing analysis outcomes, above
all regarding exomic and transcriptomic experiments.
Visualization of both kinds of omics data is frequently employed in biomedical
research to access knowledge within a genomic context, to communicate, and to
explore datasets to elaborate well-defined hypotheses. To realize this purpose, it is
necessary to adopt dedicated algorithms and tools specific for each kind of analysis.
Circos and VIsualization of VAriants (VIVA) tools allowed us a straightforward,
summarized representation of exomic outcomes, while the Omics Playground platform
produced powerful results from RNA-Seq analyses. Finally, both omics sources
represented the input of pathway analysis by ClueGO and CluePedia tools, which
produced enriched network maps useful to discover novel insights from obtained data.
Today, a huge variety of visualization tools is available to data scientists and it can be
difficult to select the right one. Data visualization users should, thus, mainly focus their
choice on ease of use and whether a tool has the features they need.
Keywords: Bioinformatics, Circos, ClueGO, CluePedia, Data analysis, Data
visualization, dbSNP, Enrichment, HeatMap, NGS, Omics Playground, Pathway
analysis, Plot, RNA-Seq, RP, Terms, Variants, VIVA, WES, WGS.
